10 Upcoming Data Science Platforms for Massive Disruption

Data Science Platforms

These upcoming data science platforms hold immense potential

Data science platforms can help companies transform their data into a significant resource in the formation of business value. Data science tools are equipped for taking care of data volumes that are too enormous for traditional databases or statistical tools. Agile development processes require a customer to express the business need and give steady input on what is being assembled. Data science teams are the same. They are best when they work intimately with individuals who really utilize the models that they build. Without data science platforms, the models built may not adequately tackle the business issue that the business is struggling with. A few data science platforms are basically about model development and contain coding language capacities to this end. Data science models are ordinarily very complex and require high-end coding abilities and frequently specialized hardware. Data scientists much of the time use numerous machines simultaneously by spreading work across them. Various advanced data science platforms don’t contain languages for composing code, but permit products like R, SAS, or Python to execute model code. All things being equal, they work as a framework of record for every one of the models being created by an entire data science team. Let’s look at some of the upcoming data science platforms that will soon create massive disruption.  

DataKitchen

Massachusetts-settled DataKitchen was founded by Christopher Bergh, Eric Estabrooks and Gil Benghiat in 2013. The organization has assembled an end-to-end data-ops platform that automates individuals, tools and environments in a data analytics company, covering everything from orchestration, testing and monitoring, to development and implementation. The innovation expects to help data analytics organizations orchestrate with their preferred tools, diminish mistakes through automated tests in the development and production pipeline, establish repeatable work environments to help teams make changes and trial without breaking production, and implement new features with the press of a button.  

Kortical

Kortical is an ML platform that is giving the data scientists control and placing them in the driver’s seat while Kortical does all the hard work. It is AutoML and much more, with full control and transparency, empowering quick experimentation across an enormous breadth of models, simple deployment with completely facilitated and scalable models in the platform and encourages collaboration and sharing of compute easily across a team. It helps with information prep, feature engineering, building ML models, hosting models that scale, with completely explainable ML.  

Tecton

Tecton just arose out of covertness in April 2020 with its data platform for machine learning that empowers data scientists to transform raw information into production-ready machine-learning features. The startup’s technology is intended to help organizations and businesses bridle and refine tremendous amounts of data into the predictive signals that feed machine learning models. The organization began with $25 million in seed and Series A financing co-driven by Andreessen Horowitz and Sequoia.  

Biofourmis

Biofourmis is a quickly developing digital health tech start-up that is revamping remote patient monitoring by integrating AI, machine learning, and real-time monitoring. They are equipped for recognizing personalized patterns predictive of a patient’s health condition and can discover driving markers of potential health deterioration. Their Biovitals machine learning platform is perhaps the most refined personalized physiological data analytics engine dependent on human physiology that forms customized health models, bringing about profoundly improved post-acute patient monitoring solutions and precise forecast of patient wellbeing deterioration before it occurs. The startup has raised a sum of $41.6M in funding over six rounds, the most recent being on May 21, 2019, from MassMutual Ventures, and Sequoia Capital India.  

Hunters.AI

What makes this data science platform one of a kind in the quickly developing field of AI and machine learning-based cybersecurity startups is the way to deal with real-time reports on Attack Intelligence, Hunting AI, and ceaseless automation with an enterprise’s existing security data. Hunters.AI produces and conveys visualized attack stories permitting companies to all the more rapidly and successfully detect, comprehend, and respond to attacks. Hunters.AI has raised a sum of $5.4M in funding over 1 round. This was a Seed round raised on May 22, 2019, driven by Blumberg Capital and YL Ventures.  

Skin Analytics

It is a UK-based platform that was established by Neil Daly in 2012. The company has created and tried an AI platform that recognizes skin disease at an early phase, to help the individuals who need clinical assistance get it sooner while giving peace of mind to the individuals who needn’t bother with clinical help. Skin Analytics likewise has a partnership with Bupa medical coverage to give remote skin evaluation services. Recently, the organization shut a £4m Series A round, which will finance expansion into the US.  

Civis Customer Science

Civis Customer Science is a single advanced data science platform that joins the best of notable innovation categories like CDPs, DMPs, identity graphs, and so on at an uncommon scale, with leading-edge data science for better decisioning and personalization.  

Zepl

Zepl is a data science platform to examine your cloud data warehouse in minutes. Companies use Zepl for a wide range of use cases, including predictive analytics, preventive maintenance, sales forecasting, marketing analytics, anomaly detection, product recommendations, security, and that’s only the tip of the iceberg. Zepl is an extensible, cloud-based data science and analytics platform for big business groups. With Zepl, teams of data scientists can utilize Python, R, Spark, Scala, and SQL to discover insights and make forecasts about their most significant business challenges, as well as package and present their discoveries utilizing built-in advanced visualizations.  

Inspectorio

Inspectorio is slowly becoming a leader in the inspection software industry. Their cloud-based  platforms are disrupting quality inspections by increasing profitability, transparency, and productivity. In the same way as other incredible platforms, Inspectorio was brought into the world from the dissatisfaction of three serial entrepreneurs who needed to manage the sluggish, manual process of quality inspections – while getting practically zero visibility. Inspectorio has raised a sum of $13.7M in funding over three rounds. Their most recent funding was raised on Jul 11, 2018, from a Series A round led by TechStars.  

SESAMm

SESAMm is a creative platform contending in the fintech business, gaining practical experience in Big Data and Artificial Intelligence for Asset Management. The organization leverages analytics and investment signals dependent on 250,000 textual data sources overall utilizing Natural Language Processing and precisely emotions analysis. The organization works with huge assets and funds managers worldwide in North America, all through Europe and Asia. SESAMm has raised a sum of €8M in funding over three rounds. Their most recent funding was raised on Apr 4, 2019.
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